Digital Analytics “Down Under” – Key Takeaways from eMetrics Sydney

Though it might be eight thousand miles away from the continental United States, my takeaways from eMetrics Sydney reveal that Australia faces the same challenges as digital analytics in the United States, and has some similarly fantastic speakers with great advice and stories to share.

Like the United States (and everywhere, really) there is a definite skills shortage for analysts in Australia – and a market willing to compensate! The Institute of Analytics Professionals of Australia‘s annual survey revealed that while the median income in Australia is $57,000, the median income for analytics professionals is $110,000. What’s more, there’s such a shortage that (from my conversations) there’s a definite opportunity for foreigners to find great roles within Australian companies. (So if you’ve been interested in a new life experience, this seems like a great time to try Australia!)

There was no shortage of great advice at eMetrics Sydney. Here were a few of my favourite takeaways:

“The stone age was marked by man’s clever use of crude tools. The information age is marked by man’s crude use of clever tools.”

The value of analytics is to allow you to quantify what would otherwise merely be anecdotes. (Chris Thornton, RAMS.) This kind of knowledge and understanding of the customer living outside Sales is actually a fairly recent development. After all, historically Sales were the ones with direct contact with the customer, and the ones who could bring back stories of what was happening “out there.” Now, analysts are able to not only identify but also quantify the magnitude of problems and opportunities.

Curiosity may have killed the cat, but it made for awesome analysts and marketers. Chris Thornton from RAMS declared it a “sign of a highly functioning marketing team”: when marketers get curious about data, it can become addictive and contagious, leading to great things within the organisation. After all, hiring analysts is not about the tools they know how to use: creativity is key.

Common sources of analytics failure. While, sadly, these are not new, Steve Bennett (News Corp) discussed common sources of analytics failure, including:

• Measuring too many things
• Measuring the unimportant
• Not measuring the important
• Measurement is not mapped to what drives the business
• Asking the wrong business questions
• Delivering flawed insights
• Not acting on the insight

It’s all about action. The value in data analytics is in the decision an executive makes based on the insight, not the data itself. And while analysts often labour over data quality and trying to perfect data capture, keep in mind that if you wait for your data to be 100% accurate, you will never do anything. You need your data to be reliable, but that may not actually require 100% accuracy. An interesting piece of (very honest) advice from Steve Bennett from News Corp was to never ask for budget for data quality. (It will never be understood, appreciated or prioritised as important by those removed from it!) Rather, incorporate that work into other, bigger projects, that are easier for business stakeholders to understand the value of, where they can see tangible results. Bennett noted that you don’t need a $100 million dollar datawarehouse to see value from analytics: Do what you can with the data, resources and tools you have, and you will see value!

“Analytics stems from a need to do more with less. After all, if you had unlimited resources, you would not need to optimise your efforts!” –Jim Sterne

Data is like diamonds. One of my favourite sessions, and definitely my favourite analogy, was Rod Bryan from Deloitte, who likened data to diamonds, for a number of interesting reasons:

• Data, like diamonds, is typically not valuable in its raw form. Rather, it requires modeling and engineering to create something of value. The value of data comes from the interpretation, insight and communication, just as diamonds require specialised cutting to reveal their value.
• Data, like diamonds, are hard to get value out of.
• Data, like diamonds, is (over?)hyped. Diamonds are, after all, incredibly common. Data too is everywhere. So it’s not having data, but what you do with it that matters.

Importance of communication. Good communication is absolutely critical for a successful analytics program. After all, finding insights in data isn’t what matters: it’s being able to communicate them – and creating a process for doing so again and again. A person can have the greatest insight in the world, but if they can’t share it with other people, it doesn’t matter. For example, think about complex statistical models and algorithms. While they may be good predictors, business users won’t buy in to something they don’t understand. Black box or very complicated models are less likely to be successful than something the your stakeholders can understand.

“There is no such thing as information overload, just bad design.” -Edward Tufte

Data visualisation. Data visualisation is an excellent example of the importance of communication! Data visualisation is not itself about insight, but rather, about communicating insight. –Paul Hodge. Hodge’s session on data visualisation was fantastic not only for the content presented live, but for the enhanced content available via his live tweetstream! I definitely recommend checking out some of the additional resources.

Advice for growing analysts. Communication skills are likewise important for the growth of your career. Rod Bryan from Deloitte noted that the best analysts often make the worst leaders because they lead without understanding how people use information. In fact, being viewed as “analytical” may not be a good thing for your career, if it means you are perceived as not business-minded. (Gautam Bose, National Australia Bank.)

Rather than technical or tool skills, Steve Bennett from News Corp advised analysts to work on business, communication and political skills to succeed. Jim Sterne noted that while analysts often consider themselves independent arbitrators, the best thing an analyst can do is have an opinion. Your value comes from your opinion, coupled with the data and analysis to back it up!

“Do not use statistics as a drunk man uses lamp posts – for support rather than illumination.” –Jim Sterne

Organisational challenges. One of the challenges of working in analytics, and especially working on analytics projects with IT teams, is that analytics is inherently different from the typical IT process. IT projects typically require a definitive outcome, while analytics is about exploration.

This is a real struggle in analytics: Rigidity is the killer of good analytics, but analytics without discipline is a mess. Creating a culture that encourages “playing” with data is a big organisational challenge, but it’s also critical to success. Businesses easily understand “reporting.” What they often fail to understand is the opportunity of analytics.

“Some people make decisions like a bladder.” (Only make quick decisions when you have to!) – Steve Bennett, News Corp

Analytics is not a cure-all. There are some things that analytics doesn’t apply to! It is not a cure for all of society’s ills. There can be a danger of users drinking too much “kool-aid” and ignoring common sense. Analytics can’t fully replace the insights of a competent decision maker’s personal knowledge & experience. (-Steve Bennett, News Corp)

Conclusion. I’m admittedly a little biased (given I was born in Australia) but if you’ve never been, I highly recommend checking out not only eMetrics Sydney, but also Australia generally! It was a great experience and an opportunity to hear from some new voices in analytics.